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Interpreting Data Using Statistical Models with Python
Course Overview
01.Course Overview (1:59)
Understanding Inferential Statistics
01.Module Overview (1:29)
02.Prerequisites and Course Outline (1:20)
03.Descriptive Statistics to Summarize Data (4:36)
04.Introducing Hypothesis Testing (5:00)
05.Lady Tasting Tea (4:50)
06.The Power, Alpha and p-value of a Statistical Test (2:33)
07.Introducing the t-test (4:04)
08.One Sample Location t-test and the Z-Test (3:13)
09.Other Types of t-tests (6:03)
10.One-way ANOVA (6:35)
11.Two-way ANOVA (2:48)
12.Pearson's Chi2 Test (4:16)
13.Module Summary (1:36)
Performing Hypothesis Testing in Python
01.Module Overview (1:15)
02.Demo Preparing Data for Hypothesis Testing (7:48)
03.Demo Performing the Independent t-test (6:33)
04.Demo Performing Welch's t-test (7:11)
05.Demo Performing the Paired Difference t-test (5:11)
06.Demo One-way ANOVA and Tukey's Honest Significant Difference Test (5:29)
07.Demo Two-way ANOVA (7:40)
08.Demo Chi2 Analysis (7:38)
09.Module Summary (1:20)
Implementing Predictive Models for Continuous Data
01.Module Overview (1:12)
02.Introducing Linear Regression (3:54)
03.Minimizing Mean Square Error (3:23)
04.Multiple Regression and Adjusted R-square (4:28)
05.Demo Preparing Data for Simple Linear Regression (5:56)
06.Demo Linear ..Techniques (4:54)
07.Demo Visualizing Correlations in Data (3:12)
08.Demo Selecting..Using Correlations (5:03)
09.Demo Selecting Mutual Information (1:40)
10.Module Summary (1:18)
Implementing Predictive Models for Categorical Data
01.Module Overview (1:40)
02.The Intuition behind Logistic Regression (6:12)
03.Logistic Regression and Linear Regression (3:00)
04.Accuracy, Precision, and Recall (5:41)
05.Demo Performing Classification Using Logistic Regression (5:49)
06.Demo Selecting..Information (6:15)
07.Summary and Further Study (1:51)
Exercise_file
05.Lady Tasting Tea
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